• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.133-153
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• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.30-38
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• 2023

As the number of old buildings subject to safety inspection increases, the burden on designated institutions and management entities that are responsible for safety management is increasing. Accordingly, when selecting buildings subject to safety inspection, appropriate safety inspection standards and appropriate technology are essential. The current safety inspection standards for old buildings give low scores when it is difficult to confirm damage such as cracks in structural members due to finishing materials. This causes the evaluation results to be underestimated regardless of the actual safety status of the structure, resulting in an increase in the number of aging buildings subject to safety inspection. Accordingly, this study proposed a thermal imaging technique, a non-destructive and non-contact inspection, to detect cracks inside finishing materials. A concrete specimen was produced to observe cracks inside the finishing material using a thermal imaging camera, and thermal image data was measured by exciting a heat source on the concrete surface and cracked area. As a result of the measurement, it was confirmed that it was possible to observe cracks inside the finishing material with a width of 0.3mm, 0.5mm, and 0.7mm, but it was difficult to determine the cracks due to uneven temperature distribution due to surface peeling and peeling of the wallpaper. Accordingly, as a result of performing data analysis by deriving the amplitude and phase difference of the thermal image data, clear crack measurement was possible for 0.5mm and 0.7mm cracks. Based on this study, we hope to increase the efficiency of field application and analysis through the development of technology using big data-based deep learning in the diagnosis of internal crack damage in finishing materials.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.637-645
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• 2023

This study was conducted to confirm the meaning and essence of the interpersonal caring experience of nursing students who participated in an enneagram-based care intervention program. The subjects of the study were nine second-year students in the Department of Nursing at a university located in the region, and data were collected from April 25 to August 26, 2022, through interview records, statements, and reflection journals. The collected data were analyzed using Colaizzi's phenomenological method. Results, It appeared in three categories and 10 topic groups 'Recognition through sharing and listening', 'Acceptance through comfort and forgiveness', 'Praise and giving hope through participation and companionship in daily life', While writing a person care reflection journal, you can realize the meaning of care through critical reflection, understand the essence of the person care experience, and confirm the vivid person care experience, and develop the ability to care for people through in-depth reflection on personal experiences, feelings, and deep understanding. As this improved and internalized care, confidence in one's own ability to care increased. Therefore, it is believed that the experience of caring for people based on the Enneagram can be confirmed, the results can be used for learning, and it will be used as educational material to perform people care, contributing to the development of people care education.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.321-332
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• 2024

Understanding the status of surface cover in riparian zones is essential for river management and flood disaster prevention. Traditional survey methods rely on expert interpretation of vegetation through vegetation mapping or indices. However, these methods are limited by their ability to accurately reflect dynamically changing river environments. Against this backdrop, this study utilized satellite imagery to apply the Random Forest method to assess the distribution of vegetation in rivers over multiple years, focusing on the Naeseong Stream as a case study. Remote sensing data from Sentinel-2 imagery were combined with ground truth data from the Naeseong Stream surface cover in 2016. The Random Forest machine learning algorithm was used to extract and train 1,000 samples per surface cover from ten predetermined sampling areas, followed by validation. A sensitivity analysis, annual surface cover analysis, and accuracy assessment were conducted to evaluate their applicability. The results showed an accuracy of 85.1% based on the validation data. Sensitivity analysis indicated the highest efficiency in 30 trees, 800 samples, and the downstream river section. Surface cover analysis accurately reflects the actual river environment. The accuracy analysis identified 14.9% boundary and internal errors, with high accuracy observed in six categories, excluding scattered and herbaceous vegetation. Although this study focused on a single river, applying the surface cover classification method to multiple rivers is necessary to obtain more accurate and comprehensive data.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.243-252
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• 2024

Among the Foley sound generation models that have recently begun to be studied, a sound generation technique using the Vector Quantized-Variational AutoEncoder (VQ-VAE) structure and generation model such as Pixelsnail are one of the important research subjects. On the other hand, in the field of deep learning-based acoustic signal compression, residual vector quantization technology is reported to be more suitable than the conventional VQ-VAE structure. Therefore, in this paper, we aim to study whether residual vector quantization technology can be effectively applied to the Foley sound generation. In order to tackle the problem, this paper applies the residual vector quantization technique to the conventional VQ-VAE-based Foley sound generation model, and in particular, derives a model that is compatible with the existing models such as Pixelsnail and does not increase computational resource consumption. In order to evaluate the model, an experiment was conducted using DCASE2023 Task7 data. The results show that the proposed model enhances about 0.3 of the Fréchet audio distance. Unfortunately, the performance enhancement was limited, which is believed to be due to the decrease in the resolution of time-frequency domains in order to do not increase consumption of the computational resources.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.17-26
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• 2024

The purpose of this study is to explore the direction of the role of lifelong vocational education as a field of lifelong education based on the content analysis of the innovation plan for lifelong vocational education and training in 2018. The conclusion is as follows. First, in terms of policy orientation, the direction of lifelong vocational education is possible to carry out life-integrated lifelong vocational education in terms of lifelong education. Second, in the education and training process, lifelong education can be carried out in specific practical competency areas in terms of lifelong vocational education. Third, in the case of the education and training system, in terms of lifelong vocational education, the philosophy of lifelong education is to establish an education system that spans the entire life. Fourth, in the case of education and training programs, various programs can be operated by type of lifelong education institution in terms of lifelong vocational education. Fifth, in the case of education and training, lifelong education can be distributed evenly across life stages from the perspective of lifelong vocational education. Sixth, in terms of the relationship with the industrial sector, lifelong education can strengthen the connection with industrial demand in terms of lifelong vocational education, and it can also strengthen the connection with government agencies. Seventh, in the case of support for the underprivileged, lifelong education is viewed from the perspective of lifelong vocational education. Free education and customized support for the underprivileged are possible at provincial and provincial lifelong education institutions and city, county, and district lifelong learning centers.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.127-131
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• 2024

SW education was conducted for slow youth learners. 6 learners participatd in 8 sessions of an introductory course using several plays and 3 learners who more interested in introductory course participated in deeper course using normal method. After education, we survey and interview from learners, instructors and heads of welfare organizations. Learners showed interest and participated in the fact that they were participating in SW education, which was widely talked about. Learners were found to be more satisfied with introductory course education using play such as board games, and although they initially appeared to participate in unfamiliar learning content with low efficacy, it was observed that their efficacy increased with repetition. Additionally, it was observed that young people with an IQ of 80 or higher had a higher level of interest or interest in SW education than those with an IQ of 80 or lower. we discussed that there were not many opportunities to directly use the SW education content for youth who are slow learners in work or real life. We suggest this should be a focus education on the use of digital media - online meeting apps, office SW etc.- to improve digital literacy for life and work and that research on this should continue.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.71-79
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• 2024

ChatGPT, an interactive artificial intelligence (AI) chatbot developed by Open AI in the U.S., gaining popularity with great repercussions around the world. Some academia are concerned that ChatGPT can be used by students for plagiarism, but ChatGPT is also widely used in a positive direction, such as being used to write marketing phrases or website phrases. There is also an opinion that ChatGPT could be a new future for "search," and some analysts say that the focus should be on fostering rather than excessive regulation. This study analyzed consciousness about ChatGPT for college students through a survey of their perception of ChatGPT. And, plagiarism inspection systems were prepared to establish an education support model using ChatGPT and ChatGPT. Based on this, a university education support model using ChatGPT was constructed. The education model using ChatGPT established an education model based on text, digital, and art, and then composed of detailed strategies necessary for the era of the 4th industrial revolution below it. In addition, it was configured to guide students to use ChatGPT within the permitted range by using the ChatGPT detection function provided by the plagiarism inspection system, after the instructor of the class determined the allowable range of content generated by ChatGPT according to the learning goal. By linking and utilizing ChatGPT and the plagiarism inspection system in this way, it is expected to prevent situations in which ChatGPT's excellent ability is abused in education.

• Journal of Digital Convergence
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• v.21 no.3
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• pp.1-14
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• 2023

This raises the question of how competitive advantage can be created, prompting firms to enhance their capacity for change. In this context, the role of knowledge creation becomes increasingly vital. This research aims to explore the role of intellectual capital and how to improve knowledge cration ability through absorptive capacity framework. It examines the links among knowledge acquisition, learning of new knowledge, knowledge creation, intellectual capital, and competitive advantage, drawing from both internal and external sources. The study focuses on small and medium-sized supplier firms in Korea, with data collected from 15 industries, totaling 106 responses. The research model employs structural equation modeling (SEM) and utilizes AMOS 22 for analysis. As anticipated, all hypotheses were supported. The study provides robust evidence that absorptive capacity is a pivotal factor in cultivating suppliers' competitive advantage. Furthermore, it posits that intellectual capital should be viewed as a criucial component of suppliers' knowledge stock, significantly enhancing the impact of absorptive capacity on their competitive edge. Future studies should aim to validate the research model in different international settings or across multinational corporations to enhance its generalizabulity.